Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm, to detect malicious nodes in an OBS network. The proposed semi-supervised model was trained and validated with small amount data from a selected dataset. Experiments show that the model can classify the nodes into either behaving or not-behaving classes with 90% accuracy when trained with just 20% of data. When the nodes are classified into behaving, not-behaving and potentially not-behaving classes, the model shows 65.15% and 71.84% accuracy if trained with 20% and 30% of data respectively. Comparison with some notable works revealed that the proposed model outperforms them in many respects.
In this work, thin films of cadmium oxide: nickel oxide (CdO: NiO) were prepared by pulsed laser deposition at different pulse energies of Nd: YAG laser. The thin films' properties were determined by various techniques to study the effect of pulse laser energy on thin films' properties. X-ray diffraction measurements showed a mixture of both phases. The degree of crystallinity and the lattice constant increase with the laser energy increase, while the lattice strain decreases. FE-SEM images show that the substrates' entire surface is uniformly covered, without any cracks, with a well-connected structure consisting of small spherical particles ranging in size from 15 to 120 nm. Increasing the laser power causes to increase the pa
... Show MoreThe influence of annealing on quaternary compound Ag0.9Cu0.1InSe2 (ACIS) thin film is considered a striking semiconductor for second-generation solar cells. The film deposited by thermal evaporation with a thickness of about 700 nm at R.T and vacuum annealing at temperatures (373,473) K for 1 hour. It was deposited in a vacuum of 4.5*10-5 Torr on a glass substrate. From XRD and AFM analysis, it is evident that Ag0.9Cu0.1InSe2 films are polycrystalline in nature, having ideal stoichiometric composition. Structural analysis indicated that annealing the films following the deposition resulted in the increasing polycrystalline phase with the preferred orientation along (112) direction. , increasing crystallite size and average grain size
... Show MoreThis survey investigates the thermal evaporation of Ag2Se on glass substrates at various thermal
annealing temperatures (300, 348, 398, and 448) °K. To ascertain the effect of annealing
temperature on the structural, surface morphology, and optical properties of Ag2Se films,
investigations and research were carried out. The crystal structure of the film was described by Xray diffraction and other methods.The physical structure and characteristics of the Ag2Se thin films
were examined using X-ray and atomic force microscopy (AFM) based techniques. The Ag2Se
films surface morphology was examined by AFM techniques; the investigation gave average
diameter, surface roughness, and grain size mutation value
The influence of bias current on the bandwidth of chaotic signals in semiconductor lasers by optical feedback has been studied experimentally and numerically. The measured data reveal that the bandwidth increase when the system becomes chaotic and this chaotic signal has a broadband spectrum so it can be used as a carrier for the quantum key. Mixing chaotic signal and quantum key make a very small change in chaotic bandwidth that does not affect the security of data transmitted.
In this paper, a construction microwave induced plasma jet(MIPJ) system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate using flow meter regulator. The influence of the MIPJ parameters such as applied voltage and argon gas flow rate on macroscopic microwave plasma parameters were studied. The macroscopic parameters results show increasing of microwave plasma jet length with increasing of applied voltage, argon gas flow rate where the plasma jet length exceed 12 cm as maximum value. While the increasing of argon gas flow rate will cause increasing into the ar
... Show MoreFe3O4:Ce thin films were deposited on glass and Si substrates by Pulse Laser Deposition Technique (PLD). Polycrystalline nature of the cubic structure with the preferred orientation of (311) are proved by X-ray diffraction. The nano size of the prepared films are revealed by SEM measurement. Undoped Iron oxide and doped with different concentration of Ce films have direct allowed transition band gap with 2.15±0.1 eV which is confirmed by PL Photoluminescence measurements. The PL spectra consist of the emission band located at two sets of peaks, set (A) at 579±2 nm , and set (B) at 650 nm, respectively when it is excited at an excitation wavelength of 280 nm at room temperature. I-V characteristics have been studied in the dark and under v
... Show MoreCdO films were deposited on substrates from glass, Silicon and Porous silicon by thermal chemical spray pyrolysis technique with different thicknesses (130 and 438.46) nm. Measurements of X-ray diffraction of CdO thin film proved that the structure of the Polycrystalline is cubic lattice, and its crystallite size is located within nano scale range where the perfect orientation is (200). The results show that the surface’s roughness and the root mean square increased with increasing the thickness of prepared films. The UV-Visible measurements show that the CdO films with different thicknesses possess an allowed direct transition with band gap (4) eV. AFM measurement revealed that the silicon porosity located in nano range. Cadmium oxide f
... Show MoreMobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
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